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2020 – today
- 2023
[j11]Pramudita Satria Palar
, Lavi Rizki Zuhal, Koji Shimoyama:
Global Sensitivity Analysis in Aerodynamic Design Using Shapley Effects and Polynomial Chaos Regression. IEEE Access 11: 114825-114839 (2023)- [j10]Pramudita Satria Palar, Lavi Rizki Zuhal, Koji Shimoyama:
Enhancing the explainability of regression-based polynomial chaos expansion by Shapley additive explanations. Reliab. Eng. Syst. Saf. 232: 109045 (2023) - 2020
- [c29]Tanguy Appriou, Koji Shimoyama:
Combined kriging surrogate model for efficient global optimization using the optimal weighting method. GECCO Companion 2020: 29-30 - [c28]Pramudita Satria Palar, Koji Shimoyama, Lavi Rizki Zuhal:
Uncertainty quantification methods for evolutionary optimization under uncertainty. GECCO Companion 2020: 1614-1622 - [c27]Timothy Man Shui Jim, Ghifari Adam Faza, Pramudita Satria Palar, Koji Shimoyama:
Bayesian methods for multi-objective optimization of a supersonic wing planform. GECCO Companion 2020: 1641-1643
2010 – 2019
- 2019
- [j9]Narendra Kurnia Putra, Pramudita Satria Palar, Hitomi Anzai, Koji Shimoyama, Makoto Ohta:
Multiobjective design optimization of stent geometry with wall deformation for triangular and rectangular struts. Medical Biol. Eng. Comput. 57(1): 15-26 (2019) - [c26]Pramudita Satria Palar, Lavi Rizki Zuhal, Koji Shimoyama:
On the use of metaheuristics in hyperparameters optimization of gaussian processes. GECCO (Companion) 2019: 263-264 - [c25]Kaifeng Yang, Pramudita Satria Palar, Michael Emmerich, Koji Shimoyama, Thomas Bäck:
A multi-point mechanism of expected hypervolume improvement for parallel multi-objective bayesian global optimization. GECCO 2019: 656-663 - [c24]Pramudita Satria Palar, Rhea Patricia Liem, Lavi Rizki Zuhal, Koji Shimoyama:
On the use of surrogate models in engineering design optimization and exploration: the key issues. GECCO (Companion) 2019: 1592-1602 - 2018
- [j8]Pramudita Satria Palar, Lavi Rizki Zuhal, Koji Shimoyama, Takeshi Tsuchiya:
Global sensitivity analysis via multi-fidelity polynomial chaos expansion. Reliab. Eng. Syst. Saf. 170: 175-190 (2018) - [c23]Pramudita Satria Palar, Koji Shimoyama:
Ensemble of Kriging with Multiple Kernel Functions for Engineering Design Optimization. BIOMA 2018: 211-222 - [c22]Pramudita Satria Palar, Kaifeng Yang, Koji Shimoyama, Michael Emmerich, Thomas Bäck:
Multi-objective aerodynamic design with user preference using truncated expected hypervolume improvement. GECCO 2018: 1333-1340 - 2017
- [j7]Nobuo Namura, Koji Shimoyama, Shigeru Obayashi:
Kriging surrogate model with coordinate transformation based on likelihood and gradient. J. Glob. Optim. 68(4): 827-849 (2017) - [j6]Nobuo Namura, Koji Shimoyama, Shigeru Obayashi:
Expected Improvement of Penalty-Based Boundary Intersection for Expensive Multiobjective Optimization. IEEE Trans. Evol. Comput. 21(6): 898-913 (2017) - [c21]Pramudita Satria Palar, Koji Shimoyama:
On multi-objective efficient global optimization via universal Kriging surrogate model. CEC 2017: 621-628 - [c20]Narendra Kurnia Putra, Pramudita Satria Palar, Hitomi Anzai, Koji Shimoyama, Makoto Ohta:
In search for a better stent: Surrogate based multi-objective optimization of stent design under influence of vessel wall deformation. EMBC 2017: 1344-1347 - [c19]Pramudita Satria Palar, Koji Shimoyama:
Multiple Metamodels for Robustness Estimation in Multi-objective Robust Optimization. EMO 2017: 469-483 - [c18]Pramudita Satria Palar, Koji Shimoyama:
Exploiting active subspaces in global optimization: how complex is your problem? GECCO (Companion) 2017: 1487-1494 - [c17]Pramudita Satria Palar, Koji Shimoyama:
Polynomial-chaos-kriging-assisted efficient global optimization. SSCI 2017: 1-8 - [c16]Pramudita Satria Palar, Koji Shimoyama:
Exploiting gradient for kriging-based multi-objective aerodynamic optimization. SSCI 2017: 1-8 - [i1]Pramudita Satria Palar, Koji Shimoyama:
Exploiting Active Subspaces in Global Optimization: How Complex is your Problem? CoRR abs/1707.02533 (2017) - 2016
- [c15]Koji Shimoyama, Taiga Kato:
Evolutionary algorithm with parallel evaluation strategy using constrained penalty-based boundary intersection. CEC 2016: 3702-3709 - 2015
- [c14]Taiga Kato, Koji Shimoyama, Shigeru Obayashi:
Evolutionary algorithm with parallel evaluation strategy of feasible and infeasible solutions considering total constraint violation. CEC 2015: 986-993 - [c13]Chang Luo, Koji Shimoyama, Shigeru Obayashi:
Effects of the number of design variables on performances in Kriging-model-based many-objective optimization. CEC 2015: 1901-1908 - [c12]Nobuo Namura, Koji Shimoyama, Shigeru Obayashi:
Kriging Surrogate Model Enhanced by Coordinate Transformation of Design Space Based on Eigenvalue Decomposition. EMO (1) 2015: 321-335 - 2014
- [c11]Chang Luo, Koji Shimoyama, Shigeru Obayashi:
Kriging model based many-objective optimization with efficient calculation of expected hypervolume improvement. IEEE Congress on Evolutionary Computation 2014: 1187-1194 - 2013
- [c10]Koji Shimoyama, Shinkyu Jeong, Shigeru Obayashi:
Kriging-surrogate-based optimization considering expected hypervolume improvement in non-constrained many-objective test problems. IEEE Congress on Evolutionary Computation 2013: 658-665 - 2012
- [c9]Koji Shimoyama, Koma Sato, Shinkyu Jeong, Shigeru Obayashi:
Comparison of the criteria for updating Kriging response surface models in multi-objective optimization. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c8]Yoshinori Andoh, Koji Shimoyama, Shinkyu Jeong, Shigeru Obayashi:
Aerodynamic optimization using building cube method and data mining with proper orthogonal decomposition. SCIS&ISIS 2012: 1882-1887 - 2011
- [j5]Seiichiro Morizawa, Koji Shimoyama, Shigeru Obayashi, Kenichi Funamoto, Toshiyuki Hayase:
Implementation of visual data mining for unsteady blood flow field in an aortic aneurysm. J. Vis. 14(4): 393-398 (2011) - [j4]Seiichiro Morizawa, Koji Shimoyama, Shigeru Obayashi, Kenichi Funamoto, Toshiyuki Hayase:
Erratum to: Implementation of visual data mining for unsteady blood flow field in an aortic aneurysm. J. Vis. 14(4): 399 (2011) - [c7]Nobuo Namura, Koji Shimoyama, Shinkyu Jeong, Shigeru Obayashi:
Kriging/RBF-hybrid response surface method for highly nonlinear functions. IEEE Congress on Evolutionary Computation 2011: 2534-2541 - 2010
- [c6]Koji Shimoyama, Kazuya Seo, Tsuyoshi Nishiwaki, Shinkyu Jeong, Shigeru Obayashi:
Material design optimization for a sport shoe sole by evolutionary computation and FEM analysis. IEEE Congress on Evolutionary Computation 2010: 1-7 - [c5]Seiichiro Morizawa, Koji Shimoyama, Shinkyu Jeong, Shigeru Obayashi:
Data mining for the investigation of unsteady flow field in a hard disk drive. NaBIC 2010: 152-157
2000 – 2009
- 2009
- [j3]Shinkyu Jeong, Shoichi Hasegawa, Koji Shimoyama, Shigeru Obayashi:
Development and investigation of efficient GA/PSO-HYBRID algorithm applicable to real-world design optimization. IEEE Comput. Intell. Mag. 4(3): 36-44 (2009) - [j2]Akira Oyama, Yoshiyuki Okabe, Koji Shimoyama, Kozo Fujii:
Aerodynamic Multiobjective Design Exploration of a Flapping Airfoil Using a Navier-Stokes Solver. J. Aerosp. Comput. Inf. Commun. 6(3): 256-270 (2009) - [c4]Shinkyu Jeong, Shoichi Hasegawa, Koji Shimoyama, Shigeru Obayashi:
Development and investigation of efficient GA/PSO-hybrid algorithm applicable to real-world design optimization. IEEE Congress on Evolutionary Computation 2009: 777-784 - 2008
- [j1]Koji Shimoyama, Akira Oyama, Kozo Fujii:
Development of Multi-Objective Six Sigma Approach for Robust Design Optimization. J. Aerosp. Comput. Inf. Commun. 5(8): 215-233 (2008) - [c3]Kaisa Miettinen, Kalyanmoy Deb, Johannes Jahn, Wlodzimierz Ogryczak, Koji Shimoyama, Rudolf Vetschera:
Future Challenges. Multiobjective Optimization 2008: 435-461 - 2007
- [c2]Koji Shimoyama, Jin Ne Lim, Shinkyu Jeong, Shigeru Obayashi, Masataka Koishi:
An approach for multi-objective robust optimization assisted by response surface approximation and visual data-mining. IEEE Congress on Evolutionary Computation 2007: 2413-2420 - 2005
- [c1]Koji Shimoyama, Akira Oyama, Kozo Fujii:
A new efficient and useful robust optimization approach - design for multi-objective six sigma. Congress on Evolutionary Computation 2005: 950-957
Coauthor Index
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